Emoji Speak Louder Than Words

February 20, 2018

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It’s only been 35 years, but emoticons and emoji have massively changed the way we communicate. A handy shorthand often attributed toScott Fahlman of Carnegie Mellon, emoticons such as 🙁 and 🙂 were used as basic sentiment markers on online forums and later in text.

Emoticons have evolved since their birth in 1982, expanding to cover a broad swathe of emotions and sentiments. And little wonder. Emoticons were a ready shorthand capable of conveying – or augmenting – meaning in short-form, character-limited communications such as text messages and Tweets. Soon enough we had a emotional lexicon of ASCII smilies running the gamut of :/ to ¯\_(ツ)_/¯ .

But our graphical intensifiers were just getting started. Fast forward to 1999, when the first emojis made their appearance in Japan. With a name meaning “picture character”, they were just that: a single-character pictographic rendering of the various forms we had been so painstakingly typing out.

Now there are hundreds of emojis, many of them encoded in the Unicode Standard for relatively seamless and system-agnostic, intelligible rendering…right?

Well, it’s not as simple as all that. Emoticons, and now emoji, bring with them their own unique set of quirks around rendering, interpretation and combination.

A picture paints 💯 words, but which ones?

Gather some English texts from a couple of hundred years ago, and you’ll find that they all have their own spellings inspired by local dialects and pronunciations.

Emoticons are somewhat the same. 🙂 :] :> 🙂 and (^-^) are in a sense different spellings of the same thing. They all render as a “smiley” face to a human, who can map the notion of happiness – and abstract human expression – much more flexibly and readily than a computer can.

A computer, on the other hand, has to figure out if something like 🙂 is actually a colon in parentheses or whether :> is the beginning of a forwarded list. Even when it’s identified an emoticon, its meaning and emotive intent has to be established. Does 🙂 mean that someone is happy? Is it intended to be ironic? Is it simply a politeness marker acknowledging someone’s response?

It can be any and all of these – context is key.

How do you solve a problem like💃?

On the plus side, emoji have helped deliver visual standardization of these graphical inflections. 🐟 is much more consistently rendered than <.))))>< (and much more recognizable).

That said, some emoji exhibit striking differences across the different platforms. The standard “smiling” face has flushed cheeks on some platforms, and the “winking” face looks positively salacious in some browsers.

Where a “g” is a “g” regardless of whether you close the bottom loop, the meaning of a given emoji is more nuanced and more open to interpretation. Metaphor and euphemism are common as well – take the 🍑 emoji, for example.

As users become more comfortable with emoji – and the emoji lexicon expands – the complexity around how these cheerful images are used is growing. Emoji may be used to stand in for a word. They may be used for emphasis, for topic-marking, for irony or as a laconic response. They can function as gestures or even as arepresentation of spatial relationships.

Emoji are also increasingly becoming compounded into words – and more. A court case recently attempted to dissect themeaning of an emoji sentence. Moby Dick (or, the 🐳) has beenreimagined entirely in emoji. Examples of grammaticality are arising. Reduplication can be used as a plurality marker or for emphasis; proximity can be used to mark possession. Directionality can be indicated by the order of emoji – although there’s still plenty of free variation going on in terms of emoji syntax.

Putting it all into 💻

Emoji aren’t a semantic free-for-all, but they’re definitely a challenge for computers (or even humans!) to read and score.

As anyone who has seen the character ⮽ knows, not all emoji render properly across all devices, platforms or programs. Inter-platform variation can introduce ambiguity that can alter the meaning of an emoji, raising challenges for computers undertaking an analysis.

Emoji are still largely used as sentiment markers, but emphatic usage is difficult to score. Emphasis isn’t linear, so while two thumbs up is more positive than one thumbs up, using seven thumbs up doesn’t mean a user is seven times more positive.

Novel coinages are also a challenge. Multiple emojis are now being used to create a single token, requiring computers to be smart about how they’re read. However, many of these combinations are heavily context-based or variable, making accurate interpretations no piece of 🍰.

Not only that, but emoji usage is also highly idiosyncratic. Emoji are frequently used in gesture-like ways to enhance or articulate emotion – resulting in extensive interpersonal variation. We can map context and proximity against user demographics, but even so there’s still some 😒 involved…no matter what the emojipedia suggests.

Tim has been at Lexalytics since the early Bronze Age. During this time, he's played an integral part as COO, developing solutions that continue to change the way natural language processing happens. He can also hold his breath for 48 minutes.